New challenges are not always best met with old tools, and as challenges go, emulating synaptic connections in a scalable system – the human brain contains hundreds of trillions of synapses – is no mean feat. Synapses do more than connect neurons, they weight how well neurons are connected through signal spiking and modulation processes thought to be the basis of human learning and cognition. While a degree of progress in the development of synaptic devices has been made using phase-change memories, Ag-Si memories and resistive memories, investigations of magnetic skyrmions suggest they may be a promising alternative.

The term skyrmion was originally used in 1962 to describe a theoretical topological object in subatomic physics. However, the concept has since attracted solid-state physicists as potentially useful in next-generation electronics and spintronics, and the first observation of a magnetic skyrmion lattice was recently reported in 2009.

“My supervisor Weisheng Zhao told me to investigate applications of skyrmions,” says Yangqi Huang, a researcher at Beihang University in China. He came upon the idea of using skyrmions in synaptic devices through discussions with members of his research group, which includes spintronics theorists, people who design devices and specialists in fabrication and circuit design, as well as people working in neuromorphic computing. “A skyrmion is a particle-like structure, so I thought it’s very similar to a neurotransmitter.”

What makes a skyrmion like a synapse?

Huang and his colleagues at Beihang University and The Chinese University of Hong Kong, Shenzhen, simulated their skyrmions as two-dimensional disks 50–60nm in diameter, where the circumferential edge and centre are opposite magnetic poles separated by a chiral domain wall. The device then comprises a ferromagnetic layer that has perpendicular magnetic anisotropy, modelled as cobalt, and a heavy metal layer modelled as platinum. Together the two components comprise a “race-track” that magnetic skyrmions can move along.

Skyrmion race tracks have been studied before as possible electronic memory components. However, by adding an energy barrier at the centre of the race track, the researchers simulated presynapse and postsynapse regions. Current flow through the heavy metal layer from one end of the device to the other injects a vertical spin current into the ferromagnetic layer, which drives skyrmions between the pre and post-synaptic regions.

In a biological synapse, prior signal activity causes changes in the number of neurotransmitter receptors, leading to “depression” or “potentiation” – weakening or strengthening of the synaptic connection. The change in the magnetoresistive properties as skyrmions move either side of the energy barrier in the proposed skyrmion synaptic device mimics this depression and potentiation. Huang and colleagues showed both short-term plasticity and long-term potentiation – synapse-like behaviour that is linked to long and short-term memory.

What is the skyrmion advantage?

The simulations suggest very low energy dissipation in the skyrmion synaptic devices, Huang tells nanotechweb.org. In addition, the threshold density to drive the skyrmions is very low, as has already been shown for skyrmions in previous theoretical and experimental studies. The result is a power consumption of just 1 pJ for each synaptic event, making it a competitive contender for synaptic devices.

“But it is only a simulation,” adds Huang, emphasising that most other synaptic devices have already been experimentally demonstrated. While the race track can be readily fabricated from metals with a capping layer to produce the energy barrier, detecting skyrmions in an electrical way is still a challenge. So far, researchers in other groups have used the Kerr effect to observe skyrmions. Huang has also begun experimental work on observing skyrmions in germanium thin films using Lorentz transmission electron microscopy, but this is limited to very thin films and work in this area is ongoing.

“Skyrmions have unusual topological properties,” says James K Gimzewski, Director of the UCLA CNSI Nano & Pico Characterization Core Facility, who was not involved with the current research. As one of the pioneers in artificial synapses based on nanostructures he adds, “It is interesting to see that they can now be used to mimic synaptic excitation and depression opening a new avenue for neuromorphic devices.”

Full details are reported in Nanotechnology.